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Building AI agents is easy. Building one you can trust with a real business workflow is harder.
I built a Freelance Admin Agent to explore that problem using Strands Agents SDK and Claude Sonnet 4.5 on Amazon Bedrock.
The working MVP takes manually provided client emails and turns them into a structured payment workflow:
→ Classifies invoice and payment emails
→ Extracts client, invoice, amount, currency, dates and contextual details using structured output
→ Stores and matches records in SQLite
→ Uses deterministic logic to identify full/short and on-time/late payments
→ Uses a second agent to draft a contextual follow-up only when needed
→ Keeps the final decision with the human through Approve / Edit / Reject
One of the most valuable parts wasn't adding another AI feature. It was finding a real reliability issue during testing: reprocessing the same email could duplicate records and inflate payment totals.
I reproduced it through repeat testing, traced the database behavior, and fixed it.
That reinforced something I'm increasingly applying to my AI engineering work:
A useful AI product isn't just an LLM call. It needs clear boundaries between AI reasoning, structured data, deterministic business logic, persistence, testing, and human control.
The next iteration will focus on stronger production safeguards, including source-grounded financial extraction, precise currency handling, stricter trust boundaries for untrusted input, and eventually live inbox integrations.
I'm interested in building more systems like this for startups and teams with repetitive workflows that can genuinely benefit from AI agents and automation.
Stack: Python · Strands Agents SDK · Amazon Bedrock · Claude Sonnet 4.5 · Pydantic · SQLite · Streamlit
The duplicate-email bug is a good reason to make ingestion idempotent at the database boundary, not just in the agent prompt. I'd use a stable email identifier with a unique constraint, then version corrected invoices so retries and real changes behave differently.
Turning raw client emails into actionable steps really trims the manual triage you normally face.
turning client emails into admin tasks is such a real freelancer pain, nice build 🔥
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So I Recently rebranded my upcoming AI Agent Harness from "Crank" to "Pixie" which is the name of my cat. Do you think it was the right decision?
Which one do you prefer? Crank or Pixie?!
Check it out here: pixie.ecnivs.com
#FreelancerLife #AIHarness #FrontendDesign #AIAgent #ArtificialIntelligence #WebDevelopment #Design #TasteTest
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Pixie gets my vote too. Naming it after your cat makes it memorable, and it feels a lot friendlier for a tool people trust with their code. Nice rebrand.
I've never made an ad like this and I'm really proud of it! It's for Cosign, an app I designed that helps users understand and manage terms and agentic permissions.
Digital consent, basically.
Every frame rendered in Blender on my M1 Max, which took a while.
Figma x Opus 5.5 x Blender
We've been building something for a while, and it's finally time to share it.
Meet Zupa, an AI tool that helps you write LinkedIn and social media posts that actually sound like you.
Most people know they should post more. The hard part is sitting down and turning a rough idea into something worth reading. Zupa takes that idea and shapes it into a post built around what makes people stop scrolling and engage.
It's made for founders, marketers, agencies, and anyone building a personal brand who doesn't have hours to spend writing.
Here's a quick look at what we've built 👇
We're opening early access now, and it's free to try. If you want a look, check out https://www.zupapost.ai/
Honest feedback is welcome too. That's how we'll make it better.
Really like the idea of using psychology to help people rewrite their posts! The UI feels thoughtful and fits the concept really well. It’s a focused tool I could see being useful in everyday writing, especially for making posts more engaging. How long did it take you to go from the initial idea to the finished website?